Multi-Domain Dialogue State Tracking with Hierarchical Task Graph

Abstract

Multi-domain dialogue state tracking (DST), which tracks user goals and intentions across multiple domains, is a core task for multi-domain task-oriented dialogue system. Previous works in multi-domain DST focus on the open-vocabulary setting to alleviate the over-dependence on pre-defined ontology. However, they come up short of modeling the relationships among domains and slots in an explicit and efficient way. In this paper, we propose a multi-domain dialogue state tracker with hierarchical task graph (DST-HTG) to address the above issues. DST-HTG uses a copy mechanism to perform DST under the open-vocabulary setting, which makes our model eliminate the dependence on pre-defined full ontology. Moreover, we extend our DST model with a hierarchical task graph which has simple structure and rich semantic information to incorporate the relationships among domains and slots into DST process explicitly and efficiently. Empirical results show that DST-HTG achieves the state-of-the-art joint goal accuracy and slot accuracy in MultiWOZ 2.0, a recently proposed multi-domain task-oriented dialogue dataset, which indicates the effectiveness of our proposed model.